一句话：提出集成于代码编辑器的主动式 LLM 编程助手 CodingGenie，可基于代码上下文自动给出并定制建议。
现有基于大语言模型（LLM）的编程工具通常需要用户显式调用，难以无缝融入日常开发流程。本文提出 CodingGenie，一个集成在代码编辑器中的主动式编程助手：它根据当前代码上下文自主提供建议，覆盖 bug 修复、单元测试生成等任务，并允许用户通过提供任务描述、选择展示哪些建议来进行定制，从而在保持主动性的同时尊重开发者意图。作者通过多个用例展示了主动建议如何改善开发者体验，并分析了引入主动性所带来的成本（如额外推理开销）。该工具已开源，作者期望它能推动主动式助手方向的进一步研究。
While developers increasingly adopt tools powered by large language models (LLMs) in day-to-day workflows, these tools still require explicit user invocation. To seamlessly integrate LLM capabilities to a developer's workflow, we introduce CodingGenie, a proactive assistant integrated into the code editor. CodingGenie autonomously provides suggestions, ranging from bug fixing to unit testing, based on the current code context and allows users to customize suggestions by providing a task description and selecting what suggestions are shown. We demonstrate multiple use cases to show how proactive suggestions from CodingGenie can improve developer experience, and also analyze the cost of adding proactivity. We believe this open-source tool will enable further research into proactive assistants. CodingGenie is open-sourced at https://github.com/sebzhao/CodingGenie/ and video demos are available at https://sebzhao.github.io/CodingGenie/.
@inproceedings{paperbot9125,
title = {CodingGenie: A Proactive LLM-Powered Programming Assistant},
author = {Sebastian Zhao and Alan Zhu and Hussein Mozannar and David Sontag and Ameet Talwalkar and Valerie Chen},
booktitle = {FSE},
year = {2025},
doi = {10.1145/3696630.3728603}
}